AXEAP: a software package for X‐ray emission data analysis using unsupervised machine learning. (21st July 2022)

• Record Type: Journal Article
• Authors: Hwang, In-Hui; Solovyev, Mikhail A.; Han, Sang-Wook; Chan, Maria K. Y.; Hammonds, John P.; Heald, Steve M.; Kelly, Shelly D.; Schwarz, Nicholas; Zhang, Xiaoyi; Sun, Cheng-Jun
• Is Part Of: Journal of synchrotron radiation. Volume 29:Part 5(2022)
• Page Start: 1309
• Page End: 1317
• Publication Date: 2022-07-21
• Subjects: AXEAP -- XES -- unsupervised machine learning -- user‐friendly interface; Synchrotron radiation -- Periodicals; Free electron lasers -- Periodicals; 539.73505
• DOI: 10.1107/S1600577522006786
• Languages: English
• ISSNs: 0909-0495

Abstract

Abstract : AXEAP, a program that can process high‐resolution emission spectrum data quickly, has been developed based on machine‐learning algorithms. Abstract : The Argonne X‐ray Emission Analysis Package ( AXEAP ) has been developed to calibrate and process X‐ray emission spectroscopy (XES) data collected with a two‐dimensional (2D) position‐sensitive detector. AXEAP is designed to convert a 2D XES image into an XES spectrum in real time using both calculations and unsupervised machine learning. AXEAP is capable of making this transformation at a rate similar to data collection, allowing real‐time comparisons during data collection, reducing the amount of data stored from gigabyte‐sized image files to kilobyte‐sized text files. With a user‐friendly interface, AXEAP includes data processing for non‐resonant and resonant XES images from multiple edges and elements. AXEAP is written in MATLAB and can run on common operating systems, including Linux, Windows, and MacOS.